Trusting AI Without Line-by-Line Review (aibuddy.software)

A recent discussion highlights the challenges of relying on traditional line-by-line code review in an era where AI accelerates code generation. Teams often fall back on this outdated safety model despite its inefficacy at AI speeds. As AI produces larger diffs and faster changes, human reviewers struggle to maintain oversight, leading to superficial reviews and an increase in potential errors. The article emphasizes that the real issue lies not with AI itself but with the failure to adapt safety processes to accommodate the rapid pace of AI-driven development. Moving forward, the focus should shift from blind trust in AI outputs to building robust validation systems that ensure AI-generated changes are effectively managed. By leveraging AI to automate the creation of tests, enhance CI pipelines, and improve observability, teams can construct a layered validation stack that not only sustains high velocity but also maintains correctness. This shift necessitates a cultural transformation, where the goal becomes not just catching bugs but enabling a system where errors are expected, quickly detected, and easily corrected, allowing for rapid and reliable deployment.